Lượng khí CO2 bình quân đầu người

import plotly.graph_objects as go
import pandas as pd
import plotly.express as px
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from matplotlib import style

df = pd.read_excel('/Users/anhle/Desktop/Lượng khí thải bình quân đầu người - bản đồ thế giới.xlsx')

fig = go.Figure(data=go.Choropleth(
    locations = df['Code'],
    z = df['Annual CO2‚ emissions per capita'],
    text = df['Entity'],
    colorscale = 'portland',
    autocolorscale=False,
    reversescale=False,
    marker_line_color='darkgray',
    marker_line_width=0.5,
    colorbar_title = 'Annual CO2‚ emissions per capita',
    colorbar_ticksuffix ='t',
))

fig.update_layout(
    title_text='2021 Annual CO2',
    geo=dict(
        showframe=False,
        showcoastlines=False,
        projection_type='equirectangular'
    ),
    annotations = [dict(
        x=0.55,
        y=0.1,
        xref='paper',
        yref='paper',
        showarrow = False
    )]
)

fig.show()

Nguyên nhân phát thải CO2

print(px.colors.qualitative.Plotly)

['#636EFA', '#EF553B', '#00CC96', '#AB63FA', '#FFA15A', '#19D3F3', '#FF6692', '#B6E880', '#FF97FF', '#FECB52']

df= pd.read_excel('/Users/anhle/Desktop/Data qq/phát thải co2 theo ngành trên toàn thế giới 2020.xlsx')
fig= px.sunburst(df, path= ['Sector','Sub-sector','Sub-sector further breakdown'], values = 'Emissions share %',
                width= 650, height= 650, color='Sector',
              color_discrete_map = {'Energy': '#FF6692', 
             'Industrial processes': '#6E899C',
             'Agriculture, Forestry & Land Use ': '#00CC96',
             'Waste': '#17BECF'})
    
fig.update_layout(title_text='Sunburst',
    margin={"r":0,"t":100,"l":3,"b":3},paper_bgcolor='rgba(0,0,0,0)',
    plot_bgcolor='rgba(0,0,0,0)',font_color='#333333')

fig.update_layout(margin=dict(t=20, b=20, r=20, l=20))
fig.show()

C:\ProgramData\Anaconda3\lib\site-packages\plotly\express\_core.py:1637: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df_all_trees = df_all_trees.append(df_tree, ignore_index=True)
C:\ProgramData\Anaconda3\lib\site-packages\plotly\express\_core.py:1637: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df_all_trees = df_all_trees.append(df_tree, ignore_index=True)
C:\ProgramData\Anaconda3\lib\site-packages\plotly\express\_core.py:1637: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df_all_trees = df_all_trees.append(df_tree, ignore_index=True)

Biểu đồ lượng khí thải CO2 ở những lĩnh vực qua các năm

df = pd.read_excel("/Users/anhle/Downloads/C02 theo lĩnh vực qua các năm.xlsx", sheet_name='World')

fig = go.Figure()
fig.add_trace(go.Scatter(x=df["Year"], y=df["Buildings"], name="Buildings", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Industry"], name="Industry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Electricity and heat"], name="Electricity and heat", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Other fuel combustion"], name="Other fuel combustion", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Transport"], name="Transport", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Land-use change and forestry"], name="Land-use change and forestry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Manufacturing and construction"], name="Manufacturing and construction", mode="lines + markers"))
fig.update_layout(
    title="World", xaxis_title="Year", yaxis_title="CO2")
fig.show()

df = pd.read_excel("/Users/anhle/Downloads/C02 theo lĩnh vực qua các năm.xlsx", sheet_name='Africa')

fig = go.Figure()
fig.add_trace(go.Scatter(x=df["Year"], y=df["Buildings"], name="Buildings", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Industry"], name="Industry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Electricity and heat"], name="Electricity and heat", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Other fuel combustion"], name="Other fuel combustion", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Transport"], name="Transport", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Land-use change and forestry"], name="Land-use change and forestry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Manufacturing and construction"], name="Manufacturing and construction", mode="lines + markers"))
fig.update_layout(
    title="Africa", xaxis_title="Year", yaxis_title="CO2", hovermode="closest", dragmode="zoom")
fig.show()

df = pd.read_excel("/Users/anhle/Downloads/C02 theo lĩnh vực qua các năm.xlsx", sheet_name='Asia')

fig = go.Figure()
fig.add_trace(go.Scatter(x=df["Year"], y=df["Buildings"], name="Buildings", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Industry"], name="Industry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Electricity and heat"], name="Electricity and heat", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Other fuel combustion"], name="Other fuel combustion", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Transport"], name="Transport", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Land-use change and forestry"], name="Land-use change and forestry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Manufacturing and construction"], name="Manufacturing and construction", mode="lines + markers"))
fig.update_layout(
    title="Asia", xaxis_title="Year", yaxis_title="CO2")
fig.show()

df = pd.read_excel("/Users/anhle/Downloads/C02 theo lĩnh vực qua các năm.xlsx", sheet_name='Europe')

fig = go.Figure()
fig.add_trace(go.Scatter(x=df["Year"], y=df["Buildings"], name="Buildings", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Industry"], name="Industry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Electricity and heat"], name="Electricity and heat", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Other fuel combustion"], name="Other fuel combustion", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Transport"], name="Transport", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Land-use change and forestry"], name="Land-use change and forestry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Manufacturing and construction"], name="Manufacturing and construction", mode="lines + markers"))
fig.update_layout(
    title="Europe", xaxis_title="Year", yaxis_title="CO2")
fig.show()

df = pd.read_excel("/Users/anhle/Downloads/C02 theo lĩnh vực qua các năm.xlsx", sheet_name='Oceania')

fig = go.Figure()
fig.add_trace(go.Scatter(x=df["Year"], y=df["Buildings"], name="Buildings", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Industry"], name="Industry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Electricity and heat"], name="Electricity and heat", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Other fuel combustion"], name="Other fuel combustion", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Transport"], name="Transport", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Land-use change and forestry"], name="Land-use change and forestry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Manufacturing and construction"], name="Manufacturing and construction", mode="lines + markers"))
fig.update_layout(
    title="Oceania", xaxis_title="Year", yaxis_title="CO2")
fig.show()

df = pd.read_excel("/Users/anhle/Downloads/C02 theo lĩnh vực qua các năm.xlsx", sheet_name='America')

fig = go.Figure()
fig.add_trace(go.Scatter(x=df["Year"], y=df["Buildings"], name="Buildings", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Industry"], name="Industry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Electricity and heat"], name="Electricity and heat", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Other fuel combustion"], name="Other fuel combustion", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Transport"], name="Transport", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Land-use change and forestry"], name="Land-use change and forestry", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["Manufacturing and construction"], name="Manufacturing and construction", mode="lines + markers"))
fig.update_layout(
    title="America", xaxis_title="Year", yaxis_title="CO2")
fig.show()

Biểu đồ biến đổi nhiệt độ

df = pd.read_csv('/Users/anhle/Desktop/Data qq/Nhiệt độ TB toàn  cầu.csv')

fig = go.Figure()
fig.add_trace(go.Scatter(x=df["Year"], y=df["GAT1"], name="Global", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["GAT2"], name="Northern Hemisphere", mode="lines + markers"))
fig.add_trace(go.Scatter(x=df["Year"], y=df["GAT3"], name="Southern Hemisphere", mode="lines + markers"))
fig.update_layout(
    title="Global average temperature anomaly relative to 1961-1990", xaxis_title="Year", yaxis_title="temperature anomaly")
fig.show()

Lượng khí thải CO2 hàng năm bình quân đầu người theo nhiên liệu

fuel_df = pd.read_csv('/Users/anhle/Downloads/per-capita-co2-by-fuel.csv')
ennity_df = fuel_df['Entity']
coal_df = fuel_df['Coal']
oil_df = fuel_df['Oil']
gas_df = fuel_df['Gas']
flaring_df = fuel_df['Flaring']
cement_df = fuel_df['Cement']
industry_df = fuel_df['Industry']
xpos = np.arange(len(ennity_df))
barWidth = 0.4
plt.figure(figsize=(10,7))
plt.bar(xpos, coal_df, color='gray', width= barWidth, label='Coal')
plt.bar(xpos, oil_df, bottom=coal_df, color='royalblue', width= barWidth, label='Oil')
plt.bar(xpos, gas_df, bottom=coal_df, color='red', width= barWidth, label='Gas')
plt.bar(xpos, flaring_df, bottom=coal_df, color='purple', width= barWidth, label='Flaring')
plt.bar(xpos, cement_df, bottom=coal_df, color='green', width= barWidth, label='Cement')
plt.bar(xpos, industry_df, bottom=coal_df, color='yellow', width= barWidth, label='Industry')
plt.xlabel('Continent')
plt.ylabel('Annual CO2 emissions per capita')
plt.title('Per capital CO2 by fuel')
plt.xticks(xpos, ennity_df)
plt.legend()

<matplotlib.legend.Legend at 0x239bc105220>

fuel_df.head(6)

	Entity	Coal	Oil	Gas	Flaring	Cement	Industry
0	Africa	0.311429	0.399546	0.234221	0.040412	0.055799	NaN
1	Asia	2.548085	1.024128	0.690949	0.025913	0.289461	0.042698
2	Europe	1.653074	2.526259	2.595303	0.114441	0.145982	0.077297
3	Oceania	3.624329	3.897421	1.914228	0.410848	0.072976	0.097380
4	America	2.070175	6.068896	4.071080	0.250474	0.237061	0.060591
5	World	1.893923	1.496614	1.001585	0.052663	0.211472	0.037443

Phát thải CO2 = không

worldMap = pd.read_csv('/Users/anhle/Downloads/Mục-tiêu-thải-ròng-bằng-không-1.csv')

px.choropleth(worldMap,
              locations="Code",
              color="Status of net-zero target",
              hover_name="Entity",
              color_continuous_scale='Cividis',              
              height=700,width = 1000
              )